Kathleen F. McCoy

Efficiently computed lexical chains as an intermediate representation for automatic text summarization

While automatic text summarization is an area that has received a great deal of attention in recent research, the problem of efficiency in this task has not been frequently addressed. When the size and quantity of documents available on the Internet and from other sources are considered, the need for a highly efficient tool that produces usable summaries is clear. We present a linear-time algorithm for lexical chain computation. The algorithm makes lexical chains a computationally feasible candidate as an intermediate representation for automatic text summarization. A method for evaluating lexical chains as an intermediate step in summarization is also presented and carried out. Such an evaluation was heretofore not possible because of the computational complexity of previous lexical chains algorithms.

Generating text from compressed input: an intelligent interface for people with severe motor impairments

Computers and computer-based technology have become an integral part of the lives of many individuals with disabilities. One of the most common activities that can be computer assisted is the generation of text. People who cannot accurately control their extremities (due to disabilities such as cerebral palsy and spinal cord injury) use computers as writing tools. People whose physical disability restricts their spoken output may use a computer as a communication prosthesis. In both cases, the generation of text is a necessary activity that can be physically demanding. It should be made as easy for the user as possible. While the standard computer keyboard is an efficient interface for able-bodied people and some disabled people, it may present significant access problems for others. In these cases some alternative interface is necessary.

Generating context-sensitive responses to object-related misconceptions

Abstract A study of transcripts of users interacting with database or expert systems reveals that users often exhibit misconceptions about the objects modeled by the systems. Simply ignoring these misconceptions may not only mislead the user, but may seriously hamper the ability of the system. This paper discusses a method for responding to such misconceptions in a domain-independent and context-sensitive fashion. The method calls for reasoning about possible sources of the misconception using a model of the user and generating a response based on this reasoning. The process is made context-sensitive by augmenting the user model with domain perspective which provides shifting highlights on the user model.

Efficient text summarization using lexical chains

The rapid growth of the Internet has resulted in enormous amounts of information that has become more difficult to access efficiently. Internet users require tools to help manage this vast quantity of information. The primary goal of this research is to create an efficient and effective tool that is able to summarize large documents quickly. This research presents a linear time algorithm for calculating lexical chains which is a method of capturing the “aboutness” of a document. This method is compared to previous, less efficient methods of lexical chain extraction. We also provide alternative methods for extracting and scoring lexical chains. We show that our method provides similar results to previous research, but is substantially more efficient. This efficiency is necessary in Internet search applications where many large documents may need to be summarized at once, and where the response time to the end user is extremely important.

Focus of attention: Constraining what can be said next

During the course of a coherent conversation or discourse, the participants their attention on some subset of their knowledge. As the discourse goes on, this focused subset may change — it may grow to include more knowledge, narrow down to include just a subset of what it originally contained, or shift (either temporarily or permanently) to a new area of the participants’ knowledge base. In this work we investigate the nature of this focusing during a discourse and its effect on a natural language generation system. Our research examines how the focused knowledge is tracked during human discourse and how changes in the focused set are marked by the human conversational partners. We hypothesize that there are several different kinds of focusing going on in discourse, and attempt to provide a unified account which can handle each. This resulting knowledge will be crucial for a generation system in deciding what to say next and in deciding how to appropriately mark unexpected changes in focus.

An intelligent tutoring system for deaf learners of written English

This paper describes progress toward a prototype implementation of a tool which aims to improve literacy in deaf high school and college students who are native (or near native) signers of American Sign Language (ASL). We envision a system that will take a piece of text written by a deaf student, analyze that text for grammatical errors, and engage that student in a tutorial dialogue, enabling the student to generate appropriate corrections to the text. A strong focus of this work is to develop a system which adapts this process to the knowledge level and learning strengths of the user and which has the flexibility to engage in multi-modal, multi-lingual tutorial instruction utilizing both English and the native language of the user.

User Interaction with Word Prediction: The Effects of Prediction Quality

Word prediction systems can reduce the number of keystrokes required to form a message in a letter-based AAC system. It has been questioned, however, whether such savings translate into an enhanced communication rate due to the additional overhead (e.g., shifting of focus and repeated scanning of a prediction list) required in using such a system. Our hypothesis is that word prediction has high potential for enhancing AAC communication rate, but the amount is dependent in a complex way on the accuracy of the predictions. Due to significant user interface variations in AAC systems and the potential bias of prior word prediction experience on existing devices, this hypothesis is difficult to verify. We present a study of two different word prediction methods compared against letter-by-letter entry at simulated AAC communication rates. We find that word prediction systems can in fact speed communication rate (an advanced system gave a 58.6% improvement), and that a more accurate word prediction system can raise the communication rate higher than is explained by the additional accuracy of the system alone due to better utilization (93.6% utilization for advanced versus 78.2% for basic).

Increasing high school girls' self confidence and awareness of CS through a positive summer experience

This paper describes the design, implementation, and impact evaluation of a summer program designed to attract high school girls to entering an information technology field for their college major. Our main contributions include an analysis of immediate and longer term surveys from both the student participants and the female teaching assistants, curriculum and pedagogy highlights of the program, and lessons learned from the planning and implementation experiences.

Topic modeling in fringe word prediction for AAC

Word prediction can be used for enhancing the communication ability of persons with speech and language impairments. In this work, we explore two methods of adapting a language model to the topic of conversation, and apply these methods to the prediction of fringe words.

Generation of Single-sentence Paraphrases from Predicate/Argument Structure using Lexico-grammatical Resources

Paraphrases, which stem from the variety of lexical and grammatical means of expressing meaning available in a language, pose challenges for a sentence generation system. In this paper, we discuss the generation of paraphrases from predicate/argument structure using a simple, uniform generation methodology. Central to our approach are lexico-grammatical resources which pair elementary semantic structures with their syntactic realization and a simple but powerful mechanism for combining resources.